| dc.contributor.advisor | 張金鶚 | zh_TW |
| dc.contributor.author (Authors) | 游適銘 | zh_TW |
| dc.creator (作者) | 游適銘 | zh_TW |
| dc.date (日期) | 2009 | en_US |
| dc.date.accessioned | 9-Apr-2010 18:40:09 (UTC+8) | - |
| dc.date.available | 9-Apr-2010 18:40:09 (UTC+8) | - |
| dc.date.issued (上傳時間) | 9-Apr-2010 18:40:09 (UTC+8) | - |
| dc.identifier (Other Identifiers) | G0094257503 | en_US |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/38843 | - |
| dc.description (描述) | 博士 | zh_TW |
| dc.description (描述) | 國立政治大學 | zh_TW |
| dc.description (描述) | 地政研究所 | zh_TW |
| dc.description (描述) | 94257503 | zh_TW |
| dc.description (描述) | 98 | zh_TW |
| dc.description.abstract (摘要) | 不動產估價一般需採比較法、收益法及成本法等三種方法查估。不動產估價最終估值決定須進行協調(reconciliation)，協調的目的係為完成關聯(correlation)之步驟，就各種方法資料之質量及優缺點進行分析。為使不動產估價對於比較法三件買賣實例，及三種方法估值採賦予權重之決定方式提供量化解釋，本文分別建立比較法內部及三種方法外部權重模型。內部權重部分，買賣實例（市場）比較法一般需蒐集數個比較標的，經調整後之試算價格決定比較價格。國外以數學計算式計算實例權重雖已相當普遍，但目前尚無應用特徵效用模式，解讀實例權重形成與比較標的內部條件之關聯。本文以2007年及2008年地價基準地6,435筆買賣實例建構特徵權重模型，發現比較法買賣實例權重受價格型態、交易日期接近性、是否屬近鄰地區、實例差異百分率絕對值加總、實例比較項目修正數、其他兩個實例相對值等自變數影響顯著。欲探討成本法估值是否與成交價存在差異，以作為外部權重設定之基礎，本文以北部地區986筆交易案例，由估價人員逐筆以成本法估計成本價格，俾與成交價格比較。發現成本價格有高估之系統性偏誤現象，分量迴歸(quantile regression)分析實證認為成本法並未因屋齡較新之建物有較高精度。另發現房地交易價格愈高、建物單價愈高、總樓層數愈高、移轉樓層愈低、建物面積愈小、建築工期愈長及利潤率愈小者；估值差異愈小。外部權重分為三部分，首先將估價過程中之諸項因子，以分析階層程序法(AHP)專家問卷，彙整各種方法權重因子；其次，基於最適加權平均模式在於使三種方法估值總誤差最小之觀點，經由數學計算方程式建構2,150筆基準地三種方法標準差及相關係數模型以計算權重。第三、為了瞭解比較估值、收益估值與土地開發分析估值之關聯，本文將2,150筆三種估價方式權重建立聯立模型，以三階段最小平方法(3SLS)進行估計。實證模型系統加權解釋力甚高，且三種方式權重之自變數多符合預期並顯著，顯見三種方式之關聯性。最後，不動產估價仍需考慮一般因素，如金融海嘯對全球金融及房地產市場，其影響力無遠弗屆，最終估值之決定即需考慮市場景氣對最終估值之影響。為探討對於(不)景氣時是否(低)高估？影響(低)高估與否之影響因素為何？本文以2002年至2004年國內某金融機構對房屋貸款20,532件之估值，以二項式邏輯特(Binary Logit)模型分析。實證結果發現於不景氣時期抵押貸款低估機率提高，景氣時期則無高估現象。綜上，本文以權重模式、估值差異及市場景氣影響探討不動產估價最終估值之形成，於權重模型建構及預測上，非如以往文獻僅對估值預測，而係就權重預測。於加權平均應用上，外生變數之迴歸係數可作為權重設定之參考。本文直接探討最終估值形成之權重核心，冀使估價之客觀性及科學化程度提高。 | zh_TW |
| dc.description.abstract (摘要) | Real estate appraisal comprises the sales comparison, income, and cost approaches to value in general. The purpose of reconciliation is to complete the procedure of correlation and analyze the qualitative and quantitative strengths and weaknesses of different approach data. In order to assist quantifiable explanation when weighted average for three comparables in the Sales comparison approach and indicated values from three approaches are applied, this paper constructs internal and external weight models respectively. For internal weight model, this paper examines the correlation between weight and internal attributes of 6,345 sales comparables from land value benchmark in 2007 and 2008 adopting the hedonic price model. The outcome shows the price type, the proximity of transaction date, inside the neighborhood area or not, total gross adjustment as %, numbers of adjustments and the attributes of other two comparables considered in one appraisal are significant on the weight of comparables. To explore whether the cost approach causes bias or not, and make it reference for establishment of external weight model, this paper compares the cost value, appraised by valuers applying the cost approach individually, from a sample of 986 transactions of properties sold in 2007 and 2008 in northern Taiwan, to sale price and finds the cost value is higher than sale price on average. It proves that the reliability of the cost approach is comparatively questionable due to its systematic bias of overestimation. With quantile regression, the outcome shows that the precision of cost value won’t increase for newer buildings. In addition, this paper finds the more the total property sales amount, the higher the unit construction fee, the higher building, the lower story, the smaller area, the longer construction years of properties, and the smaller profit rate; the smaller the bias. There are three parts for external weights. First, AHP expert questionare is adopted to combine weight factor from each approach. Secondly, based on the logic that the best way to assign weights on three appraisal approaches is to get the minimum total error, this paper calculates the standard error and correlation indicators from three approaches using 2,150 land value benchmarks. Thirdly, in order to realize the weights correlation among the sales comparison value, income capitalization value and land development analysis value, this paper builds a model based on the three-stage least squares method simultaneous equation (3SLS). The empirical result shows system weighted R2 is high and most attributes on the weights of three indication of value are significant and are consistent with expected sign, which means the model fit is good and how the weights of three methods correlate.Finally, general factor also needs to be considered in real estate appraisal. For instance, financial tsunami exerts powerful influence on financial and real estate market globally, which makes it necessary to consider real estate cylce influence when seeking the final value. In order to discuss whether the appraisal value of mortgage is smaller (greater) or not when the market is bearish (bullish) and the corresponding factors, this paper collects 20,532 mortgage appraisal value from one bank from 2002 to 2004. With Binary Logit model, this paper finds the probability of lower appraisal is greater in bear market. The outcome confirms two hypotheses of this paper. However, overestimation is not confirmed in bull market. To sum up, this thesis researches the formation of final value of real estate appraisal by discussing weight model, appraisal bias and influence of real estate cycle. For weight model construction and forecasting, this dissertation forecasts weight directly, instead of value like most literature focus. The regression coefficients estimated from factors during the procedure of each approach could serve for reference if weighted average is applied reconciling the value conclusion by valuers. By delving into the core issue of value formation, it hopes to elevate the degree the objectivity and science of real estate appraisal. | en_US |
| dc.description.tableofcontents | 摘 要 II圖目錄 VII表目錄 VIII第一章 緒 論 1第一節 研究動機與問題 1第二節 研究方法、資料範圍與限制 7第三節 研究架構及流程 9第二章 理論基礎與文獻回顧 10第一節 理論基礎 10第二節 文獻回顧 18第三章 比較法內部權重模式建構分析 29第一節 特徵權重模型影響因子 29第二節 特徵權重模型 35第三節 實證結果分析 36第四節 本章小結 40第四章 成本法估值差異－分量迴歸應用 41第一節 研究設計與敘述統計 41第二節 實證結果分析 45第三節 本章小結 56第五章 不動產估價外部權重模式建構分析 57第一節 分析階層程序(AHP)建構權重因子 57第二節 數學式建構外部權重模式 71第三節 三階段最小平方法(3SLS)權重模式 79第四節 本章小結 95第六章 房地產市場景氣對抵押品估值之影響 96第一節 假說建立 96第二節 資料分析與實證模型 99第三節 實證結果分析 108第四節 本章小結 113第七章 結論與建議 114第一節 結 論 114第二節 建 議 117參考文獻 119附錄1：不動產估價各種權重關係AHP專家問卷 124附錄2：總體面不景氣及預測準確度分析 128 | zh_TW |
| dc.format.extent | 3017708 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.language.iso | en_US | - |
| dc.source.uri (資料來源) | http://thesis.lib.nccu.edu.tw/record/#G0094257503 | en_US |
| dc.subject (關鍵詞) | 不動產估價 | zh_TW |
| dc.subject (關鍵詞) | 買賣實例比較法 | zh_TW |
| dc.subject (關鍵詞) | 估價權重 | zh_TW |
| dc.subject (關鍵詞) | 估值差異 | zh_TW |
| dc.subject (關鍵詞) | 不景氣低估 | zh_TW |
| dc.subject (關鍵詞) | Real estate appraisal | en_US |
| dc.subject (關鍵詞) | Sales comparison approach | en_US |
| dc.subject (關鍵詞) | Reconciliation | en_US |
| dc.subject (關鍵詞) | Correlation | en_US |
| dc.subject (關鍵詞) | Weight of appraisal | en_US |
| dc.subject (關鍵詞) | Appraisal bias | en_US |
| dc.title (題名) | 不動產估價最終估值之形成－權重模式、估值差異與市場景氣之影響 | zh_TW |
| dc.title (題名) | The formation of final value of real estate appraisal: Weight model, appraisal bias and real estate cycle | en_US |
| dc.type (資料類型) | thesis | en |
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